Method, system, and program product for transforming a biometric image

ABSTRACT

The invention provides a method, system, and program product for transforming a multi-dimensional biometric feature point set. More particularly, the invention provides a method for transforming a biometric image using surface folding of the image. In one embodiment, the invention provides a method for transforming a multi-dimensional biometric feature point set, the method comprising: converting the multi-dimensional biometric feature point set to a canonical position and orientation; applying a non-invertible transform function to each of a plurality of points of the biometric feature point set; and providing a transformed biometric feature point set comprising a plurality of transformed points.

BACKGROUND OF THE INVENTION

1. Technical Field

The invention relates generally to biometrics, and more particularly, toa method, system, and program product for transforming a biometric imageusing surface folding.

2. Background Art

Ensuring the privacy of personally-identifiable information is a growingconcern in today's society. Traditional authentication techniquesprimarily utilize tokens or depend on some secret knowledge possessed bya user for verifying his or her identity. While such techniques havebeen popular, they suffer from a number of limitations. Neither token-nor knowledge-based techniques can differentiate between an authorizeduser and a person having access to an authorized user's token orpassword. In addition, knowledge-based techniques may require a user tomanage multiple identities (user names, passwords, etc.), limiting theusefulness of such techniques.

Biometric authentication and identification techniques based on a user'sphysical characteristics (e.g., fingerprints, facial characteristics,retinal pattern, etc.) overcome the limitations of token- andknowledge-based techniques. As a result, biometric-based techniques arerapidly replacing token- and knowledge-based techniques. However,biometric-based authentication and identification techniques suffer fromtheir own deficiencies.

First, biometric data are secure, but not secret. That is, whilebiometric data may be unique and inextricably linked to an individual,some biometrics, such as a voice, facial characteristics, signature, orfingerprint, may be intercepted in transmission or mined from a databaseand subsequently misused by someone other than the individual.

Second, biometric data cannot be revoked or cancelled. Unlike a token orpassword, which may be revoked, reset, replaced, etc. in the event thatit is lost or otherwise compromised, biometric data are fixed. As aresult, once compromised, biometric data cannot reliably be used toauthenticate or identify the individual.

Third, biometric data may be used to track or otherwise observe anindividual without his or her consent. For example, if the samebiometric, such as a fingerprint, is used by more than one agency,application, or location, it may be possible to track an individual'smovements, transactions, etc. by sharing biometric data betweenagencies, applications, or locations.

In an attempt to overcome these deficiencies, U.S. Pat. No. 6,836,554 toBolle et al. describes a method for distorting a biometric, permittinguse of the distorted biometric rather than the original, undistortedbiometric. In the event that the distorted biometric is compromised, itcan be revoked and a new distorted biometric produced using a distortionalgorithm different than was used to produce the first distortedbiometric. However, the distorted fingerprint approach taught by Bolleet al. comprises scrambled blocks of the undistorted fingerprint. As aconsequence, a slight change in the position of a point of interest inthe undistorted biometric may result in the point of interest beinglocated in different blocks in the distorted fingerprint. This makes itdifficult or impossible for an authentication device to identify anindividual based on a distorted biometric stored in an authenticationdatabase. In addition, it may be possible to reconstruct the undistortedbiometric from a fingerprint distorted according to the Bolle et al.block permutation method, thereby jeopardizing the security of theoriginal biometric.

To this extent, a need exists for a biometric-based authenticationsystem and method that does not suffer from the deficiencies of knownsystems and methods.

SUMMARY OF THE INVENTION

The invention provides a method, system, and program product fortransforming a multi-dimensional biometric feature point set. Moreparticularly, the invention provides a method for transforming abiometric image using surface folding of the image from which thesepoints are derived.

A first aspect of the invention provides a method for transforming amulti-dimensional biometric feature point set, the method comprising:converting the multi-dimensional biometric feature point set to acanonical position and orientation; applying a non-invertible transformfunction to each of a plurality of points of the biometric feature pointset; and providing a transformed biometric feature point set comprisinga plurality of transformed points.

A second aspect of the invention provides a system for transforming amulti-dimensional biometric feature point set, the system comprising: asystem for converting the multi-dimensional biometric feature point setto a canonical position and orientation; a system for applying anon-invertible transform function to each of a plurality of points ofthe biometric feature point set; and a system for providing atransformed biometric feature point set comprising a plurality oftransformed points.

A third aspect of the invention provides a program product stored on acomputer-readable medium, which when executed, transforms amulti-dimensional biometric feature point set, the program productcomprising: program code for converting the multi-dimensional biometricfeature point set to a canonical position and orientation; program codefor applying a non-invertible transform function to each of a pluralityof points of the biometric feature point set; and program code forproviding a transformed biometric feature point set comprising aplurality of transformed points.

A fourth aspect of the invention provides a method for deploying anapplication for transforming a multi-dimensional biometric feature pointset, comprising: providing a computer infrastructure being operable to:convert the multi-dimensional biometric feature point set to a canonicalposition and orientation; apply a non-invertible transform function toeach of a plurality of points of the biometric feature point set; andprovide a transformed biometric feature point set comprising a pluralityof transformed points.

The illustrative aspects of the present invention are designed to solvethe problems herein described and other problems not discussed, whichare discoverable by a skilled artisan.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of this invention will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings that depict various embodiments of the invention, in which:

FIGS. 1A-D show the transformation of a biometric image according to anembodiment of the invention.

FIGS. 2A-B show a random distribution of charges.

FIGS. 3A-B show a mixture of Gaussian kernels.

FIG. 4 shows a flow diagram of an illustrative method according to theinvention.

FIG. 5 shows a block diagram of an illustrative system according to theinvention.

It is noted that the drawings of the invention are not to scale. Thedrawings are intended to depict only typical aspects of the invention,and therefore should not be considered as limiting the scope of theinvention. In the drawings, like numbering represents like elementsbetween the drawings.

DETAILED DESCRIPTION

As indicated above, the invention provides a method, system, and programproduct for transforming a biometric image. More particularly, theinvention provides a method, system, and program product fortransforming a multi-dimensional biometric feature point set by, interalia, applying a non-invertible transform function to each of aplurality of points in the multi-dimensional biometric feature pointset.

While described herein with reference to a fingerprint image, theinvention is applicable to the transformation of any number of biometricimages or multi-dimensional biometric feature point sets, such as afacial image or a signature. For example, in a facial image the innerand outer corners of the eyes, the tip of the nose, the bottom of thechin, etc. may be taken as the biometric feature points. For asignature, the top of each loop, the position of each pen directionreversal, and the location of each baseline crossing may be taken as thebiometric feature points. Preferably, the biometric image istwo-dimensional, although three-dimensional biometric images may also betransformed according to the invention (e.g., the 3D position of the tipof the nose, chin, etc. as determined from a 3D facial image).

Turning now to the figures, FIGS. 1A-D show various views of afingerprint image during transformation according to one embodiment ofthe invention. FIG. 1A shows a fingerprint image 100 suitable fortransformation according to the invention. In FIG. 1B, a reference point(i.e., a core 110) is identified on the fingerprint image 100.Preferably, at least one reference point is identified. Where the imageis a fingerprint, as in FIG. 1B, suitable reference points include, forexample, a core 110 or a delta 120.

In addition, a plurality of feature points 122, 123 are identified andthe position of each feature point defined relative to the position ofat least one reference point 110. This reference point does notnecessarily have to be one of the feature points. The number of featurepoints identified will vary based on the type, quality, and size of theimage. Where the image is a fingerprint, preferably between about 30 andabout 80 feature points are identified. These are commonly referred toas minutia points and consist of fingerprint ridge endings and ridgebifurcations.

In FIGS. 1C-D, the fingerprint image has been removed and feature points122, 123 are shown in relation to reference grid 130, 140 respectively.The removal of the fingerprint image 100 in FIGS. 1C-D is for thepurpose of description and simplicity. In reality, feature points 122,123 remain disposed in relation to the fingerprint image 100.

In order to affect a transformation according to the invention, eachfeature point in FIG. 1B is converted to a canonical position andorientation in FIG. 1C. This is done by rigidly rotating and translatingthe whole set of biometric feature points 122, 123. The translationparameters are chosen so that one or more of the reference points 110,120 ends up in a standard location. The rotation parameter is chosen toalign a reference orientation based on image properties with one of thecoordinate axes. A preferred method is to rotate the whole point set sothat the reflectional symmetry axis of the ridge flow pattern around thecore 110 is vertical. Another preferred method is to rotate the wholepoint set so that the line connecting the core 110 and delta 120 is at45 degrees.

In FIG. 1C, feature points 122, 123 are shown in relation tountransformed reference point grid 130. In FIG. 1D, the positions offeature points 122, 123 are transformed from those shown in FIG. 1C. Inorder to better show the transformed position of feature points 122,123, each is shown in relation to a transformed reference grid 140. Ascan be seen in FIG. 1D, the transformation of feature points 122, 123resembles a folding of the surface of transformed reference grid 130 togive reference grid 140.

The relative horizontal and/or vertical positions of feature points 122,123 may be reversed in their untransformed and transformed states, asthough the surface of reference grid 130 was folded like a sheet ofpaper. Notice also that several parts of the original grid 130 may mapto the same portion of the distorted image in FIG. 1D, such as the foldthat occurs in the upper right hand corner. Ambiguities such as thisguarantee that the distortion is non-invertible—there is no way to knowwhich of the original grid squares in FIG. 1C a point in this regioncame from.

One or more feature points may be transformed according to the inventionby adding an offset vector to the feature point's untransformedposition. An offset is computed from a distortion function, which, inturn, is calculated from a direction value and a magnitude value.Direction and magnitude values may be based on, for example, a randomdistribution of point charges, a mixture of Gaussian kernels, or apole-zero model. For example, FIG. 2A shows a three-dimensionalrepresentation of a random distribution of charges, while FIG. 2B showsthe associated two-dimensional gradient vectors. Similarly, FIG. 3Ashows a three-dimensional representation of a mixture of Gaussiankernels, while FIG. 3B shows the associated two-dimensional gradientvectors.

From functions such as those in FIGS. 2A-3B, transformational directionand magnitude values may be set. For example, using the random chargedistribution of FIG. 2B, a magnitude value may be set according to theequation:${{F(z)} = {\sum\limits_{i = 1}^{K}\frac{q_{i}}{{\left( {z - z_{i}} \right)}^{3}}}},$Here F is the height of the function in FIG. 2A which can be computedbased on the canonical position of the input biometric feature pointz=(x, y) and a random transformation key [z₁, z₂, . . . z_(K), q₁, q₂, .. . q_(K)] describing the position and magnitude of the K charges.

Similarly, a direction value may be set according to the equation belowwhich finds a unit vector in the direction of the gradient shown in FIG.2B:${\Phi_{x,y}(z)} = {\nabla\left( {\sum\limits_{i = 1}^{K}\frac{q_{i\quad}}{{\left( {z - z_{i}} \right)}^{3}}} \right)}$The new coordinates of a point become z′=(x′, y′)=(x+F(z)Φ_(x)(z),y+F(z) Φ_(y)(z)).

Alternatively, using the mixture of Gaussian kernels shown in FIG. 3B, amagnitude value may be set according to the equation:${F(z)} = {\sum\limits_{i = 1}^{K}{\frac{w_{i}}{{2{\pi\Lambda}_{i}}}{\mathbb{e}}^{- \frac{{({z - \mu_{i}})}^{T}{\Lambda^{- 1}{({z - \mu_{i}})}}}{2}}}}$wherein the random transformation key defines the parameter of thedistributions such as the weights w, covariances Λ, and centers μ of theK kernels. Similarly, a direction value may be set according to theequation:Φ_(x,y)(z)=∇F(z)Φ_(rand)(z),wherein Φ_(rand) is a random phase offset also based on the biometricfeature point's position z. Note that the same random function would beused each time and that the seed for the random number generator wouldbecome part of the transformation key.

Direction and magnitude values may be determined according to the sameor different functions. For example, the direction value may be setaccording to a random distribution of charges, and the magnitude valueset according to a mixture of Gaussian kernels. Alternatively, thevalues may be determined according to, for example, two differentmixtures of Gaussian kernels.

A preferred embodiment of the invention includes a transformationutilizing 24 Gaussians, each with the same isotropic standard deviationof 50 pixels. The centers of the Gaussians are placed randomly and eachgiven a peak magnitude of +1 or −1. The additive superposition of allfunctions is then taken to generate the function F(z). Preferably, twosuch surfaces are generated, one to choose the direction in which eachfeature point will be moved by finding the orientation of the localgradient and the second to choose a magnitude for the transformation ofeach feature point. Also, each feature point is moved in the defineddirection by at least a minimum move of 30 pixels.

Referring now to FIG. 4, a flow diagram of an illustrative method fortransforming a biometric image according to the invention is shown. Instep S1, a set of distinguished biometric feature points is extractedfrom the biometric image to represent the identity of an individual. Asnoted above, the biometric image is preferably a two-dimensionalbiometric image, such as a fingerprint image. At step S2, at least onereference point and at least one reference orientation is identified onthe biometric image. At step S3, the point set is rotated and translatedbased on the reference point and reference orientation such that it isin a “canonical” coordinate frame. Next, at step S4, an overallnon-invertible distortion function is calculated based on a provided keycontaining the relevant transform parameters. This distortion functionmay be based on one or more individual sub-functions. At step S5, thedistortion function is used to calculate a direction and magnitude foroffsetting each of the biometric feature points. Finally, in step S6 theresulting offset vectors are applied to the points to produce a new,transformed set of biometric feature points.

A biometric image transformed according to the invention does not sufferfrom the deficiencies of known methods. For example, in the case that atransformed biometric according to the invention is compromised, it maybe cancelled, revoked, or otherwise deactivated and a new transformedbiometric produced simply by altering one or more of the parameterscontained in the distortion key. When transformed with a suitablydifferent set of parameters, the resulting point set does not match witheither the original point set or with the version of the set resultingfrom the previous transform.

In addition, because transformation methods according to the inventionpermit the production of a nearly limitless number of transformedbiometrics, different parameters (keys) may be used by each individual.Even for the same individual, these parameters (keys) may be differentfor each authentication or identification system with which the user mayinteract. As a consequence, the transformed biometric image utilized byeach such authentication or identification system will be unique,eliminating the possibility that such systems may be combined orotherwise communicate in an attempt to track a user's movements,transactions, etc. without the user's consent.

Finally, the non-invertibility of the transformed biometric images ofthe present invention makes it extremely difficult or impossible toreconstruct the original, untransformed biometric image. This is asignificant advancement over known methods, greatly improving both thesecurity of biometric authentication and identification systems, and thewillingness of individuals to utilize them.

FIG. 5 shows an illustrative system 10 for transforming a biometricimage. To this extent, system 10 includes a computer infrastructure 12that can perform the various process steps described herein fortransforming a biometric image. In particular, computer infrastructure12 is shown including a computer system 14 that comprises atransformation system 40, which enables computer system 14 to transforma biometric image by performing the process steps of the invention.

Computer system 14 is shown including a processing unit 20, a memory 22,input/output (I/O) interfaces 26, and a bus 24. Further, computer system14 is shown in communication with external devices 28 and a storagesystem 30. As is known in the art, in general, processing unit 20executes computer program code, such as transformation system 40, thatis stored in memory 22 and/or storage system 30. While executingcomputer program code, processing unit 20 can read and/or write datafrom/to memory 22, storage system 30, and/or I/O interface 26. Bus 24provides a communication link between each of the components in computersystem 14. External devices 28 can comprise any device that enables auser (not shown) to interact with computer system 14 or any device thatenables computer system 14 to communicate with one or more othercomputer systems.

In any event, computer system 14 can comprise any general purposecomputing article of manufacture capable of executing computer programcode installed by a user (e.g., a personal computer, server, handhelddevice, etc.). However, it is understood that computer system 14 andtransformation system 40 are only representative of various possiblecomputer systems that may perform the various process steps of theinvention. To this extent, in other embodiments, computer system 14 cancomprise any specific purpose computing article of manufacturecomprising hardware and/or computer program code for performing specificfunctions, any computing article of manufacture that comprises acombination of specific purpose and general purpose hardware/software,or the like. In each case, the program code and hardware can be createdusing standard programming and engineering techniques, respectively.

Similarly, computer infrastructure 12 is only illustrative of varioustypes of computer infrastructures for implementing the invention. Forexample, in one embodiment, computer infrastructure 12 comprises two ormore computer systems (e.g., a server cluster) that communicate over anytype of wired and/or wireless communications link, such as a network, ashared memory, or the like, to perform the various process steps of theinvention. When the communications link comprises a network, the networkcan comprise any combination of one or more types of networks (e.g., theInternet, a wide area network, a local area network, a virtual privatenetwork, etc.). Regardless, communications between the computer systemsmay utilize any combination of various types of transmission techniques.

As previously mentioned, transformation system 40 enables computersystem 14 to transform a biometric image. To this extent, transformationsystem 40 is shown including a reference point system 42, a directionand magnitude value system 44, a distortion function system 46, and anoffset system 48. Operation of each of these systems is discussed above.Transformation system 40 may further include other system components 50to provide additional or improved functionality to transformation system40. It is understood that some of the various systems shown in FIG. 5can be implemented independently, combined, and/or stored in memory forone or more separate computer systems 14 that communicate over anetwork. Further, it is understood that some of the systems and/orfunctionality may not be implemented, or additional systems and/orfunctionality may be included as part of system 10.

While shown and described herein as a method and system for transforminga biometric image, it is understood that the invention further providesvarious alternative embodiments. For example, in one embodiment, theinvention provides a computer-readable medium that includes computerprogram code to enable a computer infrastructure to transform abiometric image. To this extent, the computer-readable medium includesprogram code, such as transformation system 40, that implements each ofthe various process steps of the invention. It is understood that theterm “computer-readable medium” comprises one or more of any type ofphysical embodiment of the program code. In particular, thecomputer-readable medium can comprise program code embodied on one ormore portable storage articles of manufacture (e.g., a compact disc, amagnetic disk, a tape, etc.), on one or more data storage portions of acomputer system, such as memory 22 and/or storage system 30 (e.g., afixed disk, a read-only memory, a random access memory, a cache memory,etc.), and/or as a data signal traveling over a network (e.g., during awired/wireless electronic distribution of the program code).

In another embodiment, the invention provides a business method thatperforms the process steps of the invention on a subscription,advertising, and/or fee basis. That is, a service provider could offerto transform a biometric image as described above. In this case, theservice provider can create, maintain, support, etc., a computerinfrastructure, such as computer infrastructure 12, that performs theprocess steps of the invention for one or more customers. In return, theservice provider can receive payment from the customer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising space to one or more thirdparties.

In still another embodiment, the invention provides a method ofgenerating a system for transforming a biometric image. In this case, acomputer infrastructure, such as computer infrastructure 12, can beobtained (e.g., created, maintained, having made available to, etc.) andone or more systems for performing the process steps of the inventioncan be obtained (e.g., created, purchased, used, modified, etc.) anddeployed to the computer infrastructure. To this extent, the deploymentof each system can comprise one or more of (1) installing program codeon a computer system, such as computer system 14, from acomputer-readable medium; (2) adding one or more computer systems to thecomputer infrastructure; and (3) incorporating and/or modifying one ormore existing systems of the computer infrastructure, to enable thecomputer infrastructure to perform the process steps of the invention.

As used herein, it is understood that the terms “program code” and“computer program code” are synonymous and mean any expression, in anylanguage, code or notation, of a set of instructions intended to cause acomputer system having an information processing capability to perform aparticular function either directly or after either or both of thefollowing: (a) conversion to another language, code or notation; and (b)reproduction in a different material form. To this extent, program codecan be embodied as one or more types of program products, such as anapplication/software program, component software/a library of functions,an operating system, a basic I/O system/driver for a particularcomputing and/or I/O device, and the like.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed, and obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to aperson skilled in the art are intended to be included within the scopeof the invention as defined by the accompanying claims.

1. A method for transforming a multi-dimensional biometric feature pointset, the method comprising: converting the multi-dimensional biometricfeature point set to a canonical position and orientation; applying anon-invertible transform function to each of a plurality of points ofthe biometric feature point set; and providing a transformed biometricfeature point set comprising a plurality of transformed points.
 2. Themethod of claim 1, wherein the non-invertible transform functionincludes a point offset direction as a first transform and a pointoffset amount as a second transform.
 3. The method of claim 1, furthercomprising: applying the non-invertible transform function to at leastone additional orientation of each of the plurality of points of thebiometric feature point set.
 4. The method of claim 1, wherein applyingincludes: applying a first transform function to a position of each ofthe plurality of points of the biometric feature point set; and applyinga second transform function to an orientation of each of the pluralityof points of the biometric feature point set.
 5. The method of claim 1,wherein the multi-dimensional biometric feature point set is selectedfrom a group consisting of: a fingerprint, a facial image, and asignature.
 6. The method of claim 1, wherein converting includes:determining a reference point and a reference orientation.
 7. The methodof claim 6, wherein the reference point includes a core of a fingerprintand the reference orientation includes an orientation of the core of thefingerprint.
 8. The method of claim 6, wherein the reference orientationincludes a direction between a core of a fingerprint and a delta of afingerprint.
 9. The method of claim 1, wherein the non-invertibletransform function includes a mixture of Gaussian kernels.
 10. Themethod of claim 1, wherein the non-invertible transform functionincludes a point potential function.
 11. A system for transforming amulti-dimensional biometric feature point set, the system comprising: asystem for converting the multi-dimensional biometric feature point setto a canonical position and orientation; a system for applying anon-invertible transform function to each of a plurality of points ofthe biometric feature point set; and a system for providing atransformed biometric feature point set comprising a plurality oftransformed points.
 12. The system of claim 11, wherein thenon-invertible transform function includes a point offset direction as afirst transform and a point offset amount as a second transform.
 13. Thesystem of claim 11, further comprising: a system for applying thenon-invertible transform function to at least one additional orientationof each of the plurality of points of the biometric feature point set.14. The system of claim 11, wherein the system for applying includes: asystem for applying a first transform function to a position of each ofthe plurality of points of the biometric feature point set; and a systemfor applying a second transform function to an orientation of each ofthe plurality of points of the biometric feature point set.
 15. Thesystem of claim 11, wherein the multi-dimensional biometric featurepoint set is selected from a group consisting of: a fingerprint, afacial image, and a signature.
 16. The system of claim 11, wherein thesystem for converting includes: a system for determining a referencepoint and a reference orientation, wherein the reference point includesa core of a fingerprint and the reference orientation includes one of:an orientation of the core of the fingerprint and a direction betweenthe core of the fingerprint and a delta of the fingerprint.
 17. Aprogram product stored on a computer-readable medium, which whenexecuted, transforms a multi-dimensional biometric feature point set,the program product comprising: program code for converting themulti-dimensional biometric feature point set to a canonical positionand orientation; program code for applying a non-invertible transformfunction to each of a plurality of points of the biometric feature pointset; and program code for providing a transformed biometric featurepoint set comprising a plurality of transformed points.
 18. The programproduct of claim 17, wherein the program code for applying includes:program code for applying a first transform function to a position ofeach of the plurality of points of the biometric feature point set; andprogram code for applying a second transform function to an orientationof each of the plurality of points of the biometric feature point set.19. The program product of claim 17, wherein the biometric feature pointset is selected from a group consisting of: a fingerprint, a facialimage, and a signature.
 20. A method for deploying an application fortransforming a multi-dimensional biometric feature point set,comprising: providing a computer infrastructure being operable to:convert the multi-dimensional biometric feature point set to a canonicalposition and orientation; apply a non-invertible transform function toeach of a plurality of points of the biometric feature point set; andprovide a transformed biometric feature point set comprising a pluralityof transformed points.